A free and fair media is critical in a healthy democracy, though while the data age has dramatically enhanced our ability to generate and share news, it has similarly enabled the rise of fake news, programmatic agendas, and media echo-chambers. The Dexter project seeks to leverage modern computational paradigms to monitor and analyze Southern Africa's digital media.
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This episode is presented in partnership with the Open Cities Lab
About William Bird
William is the Director of Media Monitoring Africa. (MMA) At MMA. William has overseen or been directly involved in over 200 media monitoring projects on subjects ranging from gender based violence, HIV, and racism to children and the media. William was appointed an Ashoka fellow in 2009 and also a Linc Fellow in 2010 for his work focused on children’s participation in the media. He is regularly accessed in the media on a range of media focused issues. William's love of media Monitoring and data saw him developing a host of databases but it wasn’t until 2014 that working with William’s dream for a central database to store all the Data MMA monitored was realised. Working with Open Up Dexter was born. With over 2 million stories it is not only an important record, but offers immense potential for our future. William’s knowledge of media monitoring and commitment to deepening democracy in South Africa and the continent has ensured his expertise is internationally recognised. In his spare time William likes to monitor the media when not otherwise distracted by his young sons.
About Dr Matthew Adendorff
Matthew is the Data Lead at the Open Cities Lab (OCL), a civic technology not-for-profit start-up in Durban, South Africa, that works to realise people-centric participatory democracy through the application of cutting edge data-science, machine-learning, and focused user-engagement. He is also the co-founder of Tenji, a high-performance data-science lab that leverages technology to power compound, evidence-based insights. He oversees the design and implementation of computational infrastructure, web app deployment, data analysis pipeline construction, and the application of algorithms for insightful processing of information. Matthew was introduced to data-science and machine learning during his studies in computational nanotechnology at the Massachusetts Institute of Technology, obtaining his PhD in 2016. Since then, he has worked to apply these methodologies to challenges in media analytics, city-centric data-science, bias detection, and socio-economic topology modelling. In his spare time he is an appreciator and brewer of beer.
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